這段代碼實用pil模塊比較兩個圖片的相似度，根據實際實用，代碼雖短但效果不錯，還是非常靠譜的，前提是圖片要大一些，太小的圖片不好比較。附件提供完整測試代碼和對比用的圖片。

#!/usr/bin/python

Filename: histsimilar.py
-- coding: utf-8 --
import Image
def make_regalur_image(img, size = (256, 256)):
    return img.resize(size).convert('RGB')
def split_image(img, part_size = (64, 64)):
    w, h = img.size
    pw, ph = part_size

assert w % pw == h % ph == 0

return [img.crop((i, j, i+pw, j+ph)).copy() \
            for i in xrange(0, w, pw) \
            for j in xrange(0, h, ph)]


def hist_similar(lh, rh):
    assert len(lh) == len(rh)
    return sum(1 - (0 if l == r else float(abs(l - r))/max(l, r)) for l, r in zip(lh, rh))/len(lh)
def calc_similar(li, ri):
return hist_similar(li.histogram(), ri.histogram())

return sum(hist_similar(l.histogram(), r.histogram()) for l, r in zip(split_image(li), split_image(ri))) / 16.0



def calc_similar_by_path(lf, rf):
    li, ri = make_regalur_image(Image.open(lf)), make_regalur_image(Image.open(rf))
    return calc_similar(li, ri)
def make_doc_data(lf, rf):
    li, ri = make_regalur_image(Image.open(lf)), make_regalur_image(Image.open(rf))
    li.save(lf + '_regalur.png')
    ri.save(rf + '_regalur.png')
    fd = open('stat.csv', 'w')
    fd.write('\n'.join(l + ',' + r for l, r in zip(map(str, li.histogram()), map(str, ri.histogram()))))
print >>fd, '\n'
fd.write(','.join(map(str, ri.histogram())))

fd.close()
import ImageDraw
li = li.convert('RGB')
draw = ImageDraw.Draw(li)
for i in xrange(0, 256, 64):
    draw.line((0, i, 256, i), fill = '#ff0000')
    draw.line((i, 0, i, 256), fill = '#ff0000')
li.save(lf + '_lines.png')



if name == 'main':
    path = r'testpic/TEST%d/%d.JPG'
    for i in xrange(1, 7):
        print 'testcase%d: %.3f%%'%(i, \
            calc_similar_by_path('testpic/TEST%d/%d.JPG'%(i, 1), 'testpic/TEST%d/%d.JPG'%(i, 2))*100)
make_doc_data('test/TEST4/1.JPG', 'test/TEST4/2.JPG')</pre>